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<p>windows下安装，去<a target="_blank" rel="noopener" href="https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/">清华大学开源镜像</a>下载，速度比较快。</p>
<p>选中Miniconda3-latest-Windos-x86_64.exe下载安装包（目前最新的是py3.9）<br>
<img src="https://img-blog.csdnimg.cn/d8d91424093149f38dbed700b5f91a53.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"><br>
或者（py3.8版本的）（由于该课程李沐用的是3.8，所以建议3.8）：<br>
<img src="https://img-blog.csdnimg.cn/d1fd289253ca43b3a6d253e3290ec0ab.png#pic_center" alt="在这里插入图片描述"><br>
下载完成之后双击安装即可，一般都选择默认配置即可<br>
<img src="https://img-blog.csdnimg.cn/851c612f28974e2d9c76bb06a5c8e2ef.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_18,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"><br>
<img src="https://img-blog.csdnimg.cn/507f19365d2148929aab11947972dc29.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_18,color_FFFFFF,t_70,g_se,x_16" alt="在这里插入图片描述"></p>
<p>安装完成后，打开anaconda prompt这个终端（安装miniconda的时候会自动安装prompt到你电脑上），</p>
<p><img src="https://img-blog.csdnimg.cn/99eaa2b8e6394a6b89f165ae805f1089.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"></p>
<p>然后分别执行如下四个命令，将conda和pip的软件源修改成为清华的源，这样的话，使用conda和pip下载安装软件包时速度会快很多。</p>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line">conda  config  --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/</span><br><span class="line">conda  config  --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/</span><br><span class="line">conda  config  --set show_channel_urls yes</span><br><span class="line"></span><br><span class="line">pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple</span><br></pre></td></tr></table></figure>
<h3 id="2、创建新的conda环境">2、创建新的conda环境</h3>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">conda create --name d2l python=3.8 -y</span><br><span class="line">//激活环境</span><br><span class="line">conda activate d2l</span><br></pre></td></tr></table></figure>
<h3 id="3、安装深度学习框架和d2l的软件包">3、安装深度学习框架和d2l的软件包</h3>
<blockquote>
<p>这里一定确保先配置好了清华镜像源，否则很慢</p>
</blockquote>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install jupyter d2l torch torchvision</span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/520b1d020d6c4ee3aab949205290bc74.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"></p>
<p>安装记事本，建议从网站上下载jupyter记事本解压后放到本地文件夹下</p>
<p><img src="https://img-blog.csdnimg.cn/9410a7e7f9cb436c9a8cdf234d256090.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"></p>
<p>在记事本目录下执行 <code>jupyter notebook</code>命令便可以在本机的8888端口打开jupyter了（一般会自动打开浏览器）<br>
<img src="https://img-blog.csdnimg.cn/f5680d86e1a1438da5ba37b92dbf90b4.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"><br>
<img src="https://img-blog.csdnimg.cn/1ea9363d48904e54b30c451da2548844.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAZ2R4ZGVreA==,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center" alt="在这里插入图片描述"></p>
<p>由此，你可以运行这本书中每个部分的代码。 在运行书籍代码、更新深度学习框架或<code>d2l</code>软件包之前，请始终执行<code>conda activate d2l</code>以激活运行时环境。 要退出环境，请运行<code>conda deactivate</code>。</p>
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